Baseband in-phase and quadrature data (IQ data) are the basis for radio frequency (RF) signal generation as well as radio frequency signal analysis. Given the trend in radio frequency applications towards higher bandwidths in general and in certain applications such as surveillance and/or data analysis towards longer record lengths, larger amounts of IQ data have to be stored and transferred. Accordingly, larger data storages as well as higher bandwidth capacities are required. Therefore, methods for compressing the IQ measurement data are of great interest wherein the respective methods also have to ensure a small deviation from the original signal when reconstructing the respective signal from the compressed IQ measurement data.
Typically, the IQ data are compressed based on the so-called μ-law compression. However, this approach effectively reduces the data fidelity of the digital data as a trade-off with reducing the number of bits required to store the respective data. Typically, compression ratios of 2:1 or 3:1 with acceptable loss of fidelity are achieved wherein an increase of 1% of the error vector magnitude (EVM) occurs.
In fact, the compression techniques used are based on retaining data in the most significant bits. However, the compression ratios achieved are not satisfying with respect to the increase in IQ data to be processed due to higher bandwidths and/or longer record lengths.
Accordingly, there is a need for a method for compressing IQ measurement data in a more effective way.